Rohini K, Shanthi V
Department of Biotechnology, School of BioSciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India.
Cell Biochem Biophys. 2018 Sep;76(3):357-376. doi: 10.1007/s12013-018-0844-7. Epub 2018 Apr 23.
The Influenza A virus is one of the principle causes of respiratory illness in human. The surface glycoprotein of the influenza virus, neuraminidase (NA), has a vital role in the release of new viral particle and spreads infection in the respiratory tract. It has been long recognized as a valid drug target for influenza A virus infection. Oseltamivir is used as a standard drug of choice for the treatment of influenza. However, the emergence of mutants with novel mutations has increased the resistance to potent NA inhibitor. In the present investigation, we have employed computer-assisted combinatorial techniques in the screening of 8621 molecules from Drug Bank to find potent NA inhibitors. A three-dimensional pharmacophore model was generated from the previously reported 28 carbocylic influenza NA inhibitors along with oseltamivir using PHASE module of Schrödinger Suite. The model generated consists of one hydrogen bond acceptor (A), one hydrogen bond donors (D), one hydrophobic group (H), and one positively charged group (P), ADHP. The hypothesis was further validated for its integrity and significance using enrichment analysis. Subsequently, an atom-based 3D-QSAR model was built using the common pharmacophore hypothesis (CPH). The developed 3D-QSAR model was found to be statistically significant with R value of 0.9866 and Q value of 0.7629. Further screening was accomplished using three-stage docking process using the Glide algorithm. The resultant lead molecules were examined for its drug-like properties using the Qikprop algorithm. Finally, the calculated pIC values of the lead compounds were validated by the AutoQSAR algorithm. Overall, the results from our analysis highlights that lisinopril (DB00722) is predicted to bind better with NA than currently approved drug. In addition, it has the best match in binding geometry conformations with the existing NA inhibitor. Note that the antiviral activity of lisinopril is reported in the literature. However, our paper is the first report on lisinopril activity against influenza A virus infection. These results are envisioned to help design the novel NA inhibitors with an increased antiviral efficacy.
甲型流感病毒是人类呼吸道疾病的主要病因之一。流感病毒的表面糖蛋白神经氨酸酶（NA）在新病毒颗粒的释放以及呼吸道感染传播中起着至关重要的作用。长期以来，它一直被认为是甲型流感病毒感染的有效药物靶点。奥司他韦被用作治疗流感的标准首选药物。然而，具有新突变的突变体的出现增加了对强效NA抑制剂的耐药性。在本研究中，我们采用计算机辅助组合技术从药物银行筛选了8621个分子，以寻找强效NA抑制剂。使用薛定谔套件的PHASE模块，从先前报道的28种碳环型流感NA抑制剂以及奥司他韦生成了三维药效团模型。生成的模型由一个氢键受体（A）、一个氢键供体（D）、一个疏水基团（H）和一个带正电荷基团（P）组成，即ADHP。使用富集分析进一步验证了该假设的完整性和重要性。随后，使用通用药效团假设（CPH）建立了基于原子的3D-QSAR模型。发现所开发的3D-QSAR模型具有统计学意义，R值为0.9866，Q值为0.7629。使用Glide算法通过三阶段对接过程完成了进一步筛选。使用Qikprop算法检查所得先导分子的类药性质。最后，通过AutoQSAR算法验证先导化合物的计算pIC值。总体而言，我们的分析结果突出表明，赖诺普利（DB00722）预计与NA的结合比目前批准的药物更好。此外，它在结合几何构象方面与现有NA抑制剂的匹配度最佳。请注意，文献中报道了赖诺普利的抗病毒活性。然而，我们的论文是关于赖诺普利抗甲型流感病毒感染活性的首次报道。这些结果有望有助于设计具有更高抗病毒疗效的新型NA抑制剂。
